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This paper addresses the challenge of co-designing morphology and control in soft robots via a novel neural network evolution approach.
Unshackling evolution: evolving soft robots with multiple materials and a powerful generative encoding
Nick Cheney, Robert MacCurdy, Jeff Clune, and Hod Lipson · 2014
Earlier work this paper cites.
Titan: A parallel asynchronous library for multi-agent and soft-body robotics using nvidia cuda
Jacob Austin, Rafael Corrales-Fatou, Sofia Wyetzner, and Hod Lipson · 2020
Earlier work this paper cites.
Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan Barron, and Ren Ng · 2020
Cited alongside, same era.
A legged soft robot platform for dynamic locomotion
Boxi Xia, Jiaming Fu, Hongbo Zhu, Zhicheng Song, Yibo Jiang, and Hod Lipson · 2021
Cited alongside, same era.
Evolution through large models
Joel Lehman, Jonathan Gordon, Shawn Jain, Kamal Ndousse, Cathy Yeh, and Kenneth O Stanley · 2023
Later among the works it cites.
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